DocumentCode :
251741
Title :
Reducing Costs in Cloud Application Execution Using Redundancy-Based Scheduling
Author :
Vieira, Cristiano C. A. ; Bittencourt, Luiz F. ; Madeira, Edmundo R. M.
Author_Institution :
Fac. of Comput., Fed. Univ. of Mato Grosso do Sul, Campo Grande, Brazil
fYear :
2014
fDate :
8-11 Dec. 2014
Firstpage :
117
Lastpage :
126
Abstract :
Public providers around the world offer computing, storage, and communication services as virtual machines in a pay-per-use model. From the user perspective, it is important to choose providers and charging models to run distributed applications with quality of service at lower costs. In this work, we introduce an innovative strategy to decrease the cost of VM requests scheduling on different public cloud providers. The mechanism is based on redundancy with a mixed utilization of reserved and spot virtual machine (VM) instances, and it allows the balancing between cost and availability. We implemented a QoS-aware architecture that allows the scheduling of applications considering different VM charging models. Then, we propose an integer linear program (ILP) and a heuristic algorithm to compute the QoS-aware scheduling. Experimental results show that the proposed approach computes schedules with smaller costs than alternative approaches.
Keywords :
cloud computing; cost reduction; integer programming; linear programming; quality of service; scheduling; virtual machines; ILP; QoS-aware scheduling architecture; VM instance; VM requests scheduling; cloud application execution; communication service; computing service; cost reduction; heuristic algorithm; integer linear program; pay-per-use model; quality of service; redundancy-based scheduling; storage service; user perspective; virtual machines; Cloud computing; Computational modeling; Processor scheduling; Quality of service; Redundancy; Scheduling; Virtual machining; Cloud Computing; Quality of Service; Scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Utility and Cloud Computing (UCC), 2014 IEEE/ACM 7th International Conference on
Conference_Location :
London
Type :
conf
DOI :
10.1109/UCC.2014.20
Filename :
7027487
Link To Document :
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